{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 波士顿房价预测"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sklearn.datasets as datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "boston = datasets.load_boston()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['data', 'target', 'feature_names', 'DESCR'])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['CRIM', 'ZN', 'INDUS', 'CHAS', 'NOX', 'RM', 'AGE', 'DIS', 'RAD',\n",
       "       'TAX', 'PTRATIO', 'B', 'LSTAT'], dtype='<U7')"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "boston.feature_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = boston.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "target = boston.target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train,x_test,y_train,y_true = train_test_split(train,target,test_size=0.1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import LinearRegression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "linear = LinearRegression()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "linear.fit(X_train,y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pre_linear = linear.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[19.72478817  9.97483606 24.4042948  38.55560865 15.88898484 37.66227845\n",
      " 35.53830409 23.66756669 32.81532126 20.54542523 17.33555155 33.67843198\n",
      " 15.14775644 15.86365651 20.900551   31.33227988 25.18089905 29.64208174\n",
      " 22.43258128 20.05220055 32.86969365 22.19703889 16.81417618  9.55356902\n",
      " 18.09443385 25.66682402 13.30135994 27.75551664 17.06711549 41.85183411\n",
      " 21.97015006 15.57599842 18.36772765 20.76659942 30.7662491  19.21889848\n",
      " 29.93869681 31.41049199 16.17936793 17.22654478 27.15797338 17.58754308\n",
      " 21.41818245 10.18387082 11.3472705  20.36387059 16.46135664  8.77961975\n",
      " 25.03434211 28.20422924 17.26743862]\n"
     ]
    }
   ],
   "source": [
    "print(y_pre)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[19.1  9.7 22.6 44.8 17.4 37.6 33.4 21.7 33.1 13.1 18.1 32.  16.2 17.6\n",
      " 19.6 29.1 24.  30.1 21.2 19.5 36.4 21.1 19.3  7.2 16.  23.3 12.8 26.6\n",
      " 10.2 48.5 21.4 15.6 15.4 19.3 32.5 27.1 34.9 29.9 17.3 19.4 27.1 19.6\n",
      " 21.2 23.1 12.7 16.2 13.4 14.4 29.6 28.7 17.4]\n"
     ]
    }
   ],
   "source": [
    "print(y_true)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x21760ce0da0>"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_pre_linear,label='linear_pre')\n",
    "plt.plot(y_true,label='true')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import explained_variance_score\n",
    "from sklearn.metrics import mean_absolute_error\n",
    "from sklearn.metrics import mean_squared_errorb\n",
    "from sklearn.metrics import median_absolute_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "linear_EV = explained_variance_score(y_true, y_pre_linear)\n",
    "linear_MAE = mean_absolute_error(y_true, y_pre_linear)\n",
    "linear_MSE = mean_squared_error(y_true, y_pre_linear)\n",
    "linear_medAE = median_absolute_error(y_true, y_pre_linear)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Linear解释方差： 0.833109762697497\n",
      "Linear平均绝对误差： 2.4706711882703143\n",
      "Linear平均平方误差： 1.4330723158814394\n",
      "Linear中位绝对误差： 12.798357377376588\n"
     ]
    }
   ],
   "source": [
    "print(\"Linear解释方差：\", linear_EV)\n",
    "print(\"Linear平均绝对误差：\", linear_MAE)\n",
    "print(\"Linear平均平方误差：\", linear_medAE)\n",
    "print(\"Linear中位绝对误差：\", linear_MSE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# -----------------------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import Ridge"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "ridge = Ridge()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,\n",
       "   normalize=False, random_state=None, solver='auto', tol=0.001)"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ridge.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pre_ridge = ridge.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2175ffb5a90>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_pre_ridge,label='ridge_pre')\n",
    "plt.plot(y_true,label='true')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "ridge_EV = explained_variance_score(y_true, y_pre_ridge)\n",
    "ridge_MAE = mean_absolute_error(y_true, y_pre_ridge)\n",
    "ridge_MSE = mean_squared_error(y_true, y_pre_ridge)\n",
    "ridge_medAE = median_absolute_error(y_true, y_pre_ridge)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ridge解释方差： 0.833109762697497\n",
      "ridge平均绝对误差： 2.4706711882703143\n",
      "ridge平均平方误差： 1.4330723158814394\n",
      "ridge中位绝对误差： 12.798357377376588\n"
     ]
    }
   ],
   "source": [
    "print(\"ridge解释方差：\", ridge_EV)\n",
    "print(\"ridge平均绝对误差：\", ridge_MAE)\n",
    "print(\"ridge平均平方误差：\", ridge_medAE)\n",
    "print(\"ridge中位绝对误差：\", ridge_MSE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# -----------------------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.linear_model import HuberRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "huber = HuberRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "HuberRegressor(alpha=0.0001, epsilon=1.35, fit_intercept=True, max_iter=100,\n",
       "        tol=1e-05, warm_start=False)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "huber.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pre_huber = huber.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2175ee19f28>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jc9kIuO3Ey+aQC5Pe0f+CrlWgmAKXn2haReQZ6VKPtTupdEHXNMn8tnuhUuTpQ//M3/3gHH/+yCmS+VKPF7+JMIS8nyyXmgh9wGUj6LEzZ46hM+khy5pYtCExRNvpJ5pRgp6uCnqLk0pKZC7BA88m+eCPv4lWKfK008PZH36Zj5QjAOwZ9vELt4z1cvWbh1xNhC6luira6OgeekHaGXDaCbjtRFPm1CKT3tH/EXpN69xopgBAqhMfs5xHaEUuZOy84batfPC1t5DdcQ+v9z3Pt99/NwDzmTYevEnnGJaLVlYbpP1ATYTuc9nwu+3MFvUYar1aLqlpuPzkWq/CZIX0v6DX9HGJ6QKcrBhRUouTSq8STeLlvfdex6+8ZCdbbn89tnyUnfljANWI36QLGBE6QKZPfPQaD93rtBJ025nJG4K+TiP0730MPv/z1asLk43FJhD0hda5Md1Dn+8kQjcEXXoIuvUPgL3/ASw2bGceJuixmxF6N6ndDO0XH10XdM3qxGmzEnDbmcpb1WPrVdCnj0E5BxNPrPVKTFZA/wu6brkUbV5SBVWdN1/dmMo2f11OXfZnhBePQz8J3UHY8VI4+Q3CHgexrCnoXSMbA3TfPNsnqYulHAA2h6oSDXrspDUjw2odWi5SwuwJ9fX5H6ztWkxWRP8Lum65JDR39a5oqXPLRXP5EbUbdNffB7Mn2Oecq0b8Jl0gNw/B7errfslFL6s9G4dLHXsBt50SNqTVsT4j9PTMwv7FBVPQNyKbRtCjZVf1rrlCB5kGRqdFV6D+/hteDcBP8RTzZoTePbIxGLxefd03gq4idLtLRegB3bqr2NZpT/S5k+p29FaYONz6CtZkXdL/gq5bLrMldakrBMwUOvAx9UjF4g7W3x/eDUP7OJj/cXWT1aQLZKMwsEU1UesXy6VcQEPgcqpgIuBWVt+6FfRZXdDveCdoJbj847Vdj8my6X9BLyRBWJnTRXw85Cae19TAiw4sF7sntPSxG+5jV/Yo5ew80hx8ce1IqbJcPGHV3bJfIvRSjiIOfC4l5EaEXrR41qeHPntCfaDe+Dqw2EwffQOyCQQ9peegq6rOXYM+ktVhva0tlwIOfF7v0seuexVWWeFF8lh1o9XkGihmVF8ddxi8g30VoRewM+BSqYpBjxJ0NbVonUboQzeA0wdbXwTnv7/WKzJZJv0v6PlktUrUbhWMh9wkcqX2Qy7yCRLSi99IWaxl8DoAxkS0s9RFKeFffwsumZewDTFy0D0R8A71T4RezpHXy/5hIULPC9f6FnSAnS+Dq88spP2abAj6X9D11rmxdJGQx0HQbSeRKyEdvpaXvVouQUJ6qlFVHZ4ImsXOqIh1VlyUjcFTn4NTD6/89+hnjBz0PrNcZLlAXtrxOZWgexxWbBZBTrjWn+WSjUFmBgZ1Qd/1MtXO+OK/r+26TJbFJhD0lB6hF4j4nAQ9diqaRGuzMVXJxklSU1RUixCUvFvY0mmEntQHY3ShpP3QiRm+e2L6mt9nXWGU/ddaLn2wN6EVc+SkKvsHEEIQ9NhVc7j1FqEbG6JD+9TttjvB6oALpu2ykeh/Qc8nVKfFTJGI11G97C3ZPFBqnpZVyc2rKlGPo+HjcmCMURHrLNOlKuiJZS9/MX/xndP8r++cueb3WVcYvdA9YfAM9k0/l3Ixpzx050IPPL9bLy5aLUH/7kfhW/+j/fOMgiLDcrG7Yfx2c2N0g9H/gl5QvdCj6SIRn6Mm06DNxlQ+QRJv9fmLsQa3soUOBT0xUX3Pa2UuVSDeb/nv2UUeOvRFPxetqDx0I0IHCLrtJLVVLCw69Q14+n+rEX+tmDsFdg8Eti3ct+un1OhF4wPXZN2zCQRdWS6xTJGw11Hd5CyI1mmLlkKCpPQQaOShA7bgOFvEPDG9g2NLklfV7TUKupSS8fSzbM88e03vs+4wPHRXELwR/b6N76PLUr7aOtcg4LYTr+gRejuR7QapaXXczR5v/bzZE2qz31IjCTtfBlKDi4/1do0mXaO/BV1KyCcpOwZIF8p1lkuuVaaBlNiKqeYeOiD8W3GKEoVkB42kDMsld202QrpQ5vcsX+T92v+mXFkFMVgtcjFVkWu1KcsF+mJjVJZy1da5BmpqkR2Q1UrSnlEpLzQ6u9Rmc3P25IJ/bjB+EGwu03bZQPS3oJfzoJXIokqvIz5nVdCztBD0UhaLLJOUzS0X/KMACCP6bkWXIvS5dJFh5gmTJJ7ro2lJ2ZjaEIUay2Xjd1yU5TwFFrJcAIIeB9HVmlqUnQP0zeVW2Sr5pAo6DP/cwOZUm6NmX5cNQ38Lup5DmxZK0MM1EXpaOtWmqFZZ+jpdeBMtPHT8WwGwZSbbr6NLHvpsMs+QSBARqf5q3ZuLKf8cVJYL9IXlIsr5ujx0UJuisWIHzeG6QWpK3ToGWtdAzJ1Wt4sjdFDpi9PP9cWexmagvwVd7+MS11QvjUGfA5/ThtUiSGt6lNQo00UX3pJtAJu1yZ/Ir0bPufNtUgilVBG6sEKlUG2puhLm4zHcoohfZImn1lna27WQjaoMF1BRoWOgLwTEUilQkIsidLddXR1C7yP0tH5s3nAfJCcgfrnx84wMl8Eblj6286fU7cUfdn99Jl2nvwW9oIQ5XlEnUNjrRAiB32UjUTH6Ujc4qXRBrzj9zd/bN0IFK77CTOs1ZKNKyCN76957JWRjC/ZOer7Nz91IZOcXLBdQG6N9EKFbK4UlWS4Bt53Magv6Ta9Tt82i9NkTKuc8tHPpY1tvA7vX9NE3CH0u6MpyiZUNQV9okhQvt/Axjc3Lxa1za7FYyToihMpzlFptUBoboiM3qttrEPRCfKr6dT7RR8VFtZYL6OX/G99Dt2oFyhYHTpu1el/AbScrV2nIRUo/Rna/QrddmmSrzJ6EyHVqU3oxVjtsf7Hpo28Q2gq6EMIlhHhCCHFUCPG8EOIP9Pt3CSEeF0KcFkI8IIRoXIGzluiWy0zRid2qInNQJ9V8K0HXRXdJ69zFT3NvYYuIEc+22KBMKEE/ND9U994roZJcEPFSauMLHqCGQBTTUNvV0jO48S0XrYJVlpFWV93dQc9qRuhT4A6pvkXb7mgeoc+dXLohWsuul6koPtVHQUSf0kmEXgDukVLeAtwKvFoI8WLgT4E/l1JeB8wDv9q7Za4QfbjFdNFO2OuoTh7yu+3EqlOLmgt6w9a5NZS8W9pXi+oR+pcu+NT315K6mFmwWSrpjW9JAPVl/wb9YLno80SxOevuXnXLxbdFfb39JTBzbGmRUDEL8xergn45luXQyUV2nuGjm1H6uqetoEuFcW1o1/9J4B7gK/r9nwde15MVXgu65TKZcxD2LpxYAbeduWIHgu5tHaHjH2NURImlWxQXJa+gWeyck6N1770S7LkakVsvedqaBscebJwt1AnVTou1gq53XNzI/VxKuqDb3XV3Bzx2snKVBD01Db5h9fX2F6vbS4/XPyd6GpBVQf/U98/yq597kkvRmmSB0VuUZWMK+rqnIw9dCGEVQhwBZoBHgLNAXEppNAOfALb2ZonXgG65TOTsDPoWHKGA285sQfcLG/iYMh8nK50M+Dwt394a3IpXFEglY82flLhCwT1CQuoR+jX0KHEV5khbA2gIrPkWP3M1OXcI/ulX4PS3Vvb62rJ/A8+gmpjThVYJa4YeoVvs9ZZLfYTeYw89PaWmQIHqb26xLy0wWtSUayqRR5Pw6R+cXXiO1QY77zI3RjcAHQm6lLIipbwVGAfuAPY3elqj1woh3iWEOCyEODw7u8q+byEJdg9z2Up1QxTUSTWdNwR9aZRUbtVpsQZXWPW9yEebpIMBJK+SdAyT1Iub5DVYLt7yPBnHEBnLAPbCOumvMXFY3Rq5zMslt2C5/GQirvLrq7noG9hHNwTdUR+hO21WhN2JhqW3EbqUauizb0R97/DA2K1LffTZkyqlNrwHgOmkutr8p8MTzKZqrjy33QGxs2Z/9HXOsrJcpJRx4FHgxUBQCGFsi48DDUsmpZSfllIelFIeHBoaupa1Lp+CPtwiXSBSY7kEPXZSWvNN0XJmnoT0Nu6FXoNnUE2p1xItqkWTE0QtgxSxk5MOsqmVRdaZQpmInKfgGiRjDeAurRNBv/q0uo2dbf28ZuiiXXIGefOn/p2//O7p/ij/1wXdtkjQAYJuZ++nFuUTag2GoIOyXa4+vWAHgdrsDO8GmzofZlJ57tgZplTR+OyPzi88zz+ubs2NUXjmi/CJ/XDsobVeyRI6yXIZEkIE9a/dwH8AjgOHgF/Un/Z24MFeLXLF5JNozgEyxQqRRZZLtsVlbyWXIImneZWojj2kDvKm5f96UdGkVHZCEg/Z5Mqizrl0gUGRQPMMkXeE8JTXQXtZKeGKIejnVvYeuuVyKeckX9J47kpiIULfyKmLumhaHUttu4Dbrk8t6qHlYuSgG5YLwPaXqlF/xocw1E0pqmiS2VSBO3aFec2BUb7w7xdJ5kv175PqoDK637nyFKSuwj/9Mjz4biisn2ElnUToo8AhIcRPgCeBR6SUXwf+G/A7QogzQAT4TO+WuUIKSco25V0vtlwK2JHC0rhSNDev93Fpk4k5oDY67c3K/zNzUClysRxk0OcgKb0U0yuLrOdSeYZIYBkYpuQM49eSVLTubxqePHmMf/2Ld5MvdNgWODOjBgpHVyjouXmwezkdU9sxJyZTSM/G77go9cZbdtfSCD3gsZNr1UuoGxiCXhuhb7tT3Ro+ermoPoh1/zyaKaBJGPE7+fWX7yFVKHP/jy+p5+rHerWdwCYmPneVmGsb8u7/As/cD39794L1uMZ0kuXyEynlC6WUL5BSHpBS/qF+/zkp5R1Syr1SyjdJKTvoI7vKFFIUdEGP1Ai6aqErqDSZWmQpJJWH3sZyweYgLoK4800Ocj1l8Uw+wMEdYRJ4qWRWJujz8zGcooQ9MIrmDhMWKTXsusucO/R5fj7+Rc4c+V77JxuR3p57VWn5StoaZGPgCXN6WkU5qUKZiaI+mHsDWy6lvAoUHK7GEXqm14KeaiDo3ogq7zd89NhZNWZOF/QZ3T8fGnBx83iAl103yGd+eJ58qQID+vuYETrJuSlOZX0cveF98I7/owayfOaV8L0/Ux0u15D+rhTNJ8lZlDgstlwAylZPw8teazGpeqG3sVwA4vYhfMUmZfi6oB/P+tgx6KFg8yH03PjlktHL/t2hUYR3kBCpznqxLwMpJbkZFWlnTj7a/gVXnlaZEze+Vn0/f2H5PzQbBXeIM7Np9DIBjs0W9X4uG1fQ87qgO5sIes+nFqVVkPFUzMGPz9XYfNtfrFIXtUrNlKLrAeWfg4rQAX7j5XuYSxf46tMT4PSrARhmhI6zGCMqB/inw5dV9s+v/xAOvAEOfRS++PqVp/B2gf4W9EKSjNE6d1EeOkDR2iBClxJ7KUWS9puiAGnnMMFyE+HRq0QvlyOMBdxojgD20soEvRhXkZEvMobFN4hdVEjFuyt4xyaTDJb0nzPZojufwZWnYMsBGNa79EVXsDGaW4jQb98RRgg4Ppnc8MVF+aw6rpzupYKuphY5e+uhp6bA5uaPHpngo/+nZrjFjpeqHkczx/WURaHK/lnIcBn2q/2ll+yJcMt4gE997xxlTSof3YzQ8ZbnicoA/3rkKrliBdxBeOPfwcs/AOe/D4kWWW89ps8FPUUa5WGGG0ToBUuDy95iGgsaGeHFbbfSjoJ7C4NaFNmoCCZ5Bc3iIMoAowEXFk8QV2VlJ3FZv4S2+UdwDKhsoUyXG3QdOjHDDqF+zq7cc8hyCx9d02DyKIzdVk15W9HGaDaG5o5wdjbNzeMBdka8StA9gxs6Qi/klf3kdHmXPBZw20lpTmShlxH6DPiGuZrIczVeY4VVC4z+XQl6aIdKaQSmkypCH/Kp4EcIwW/89B4uxbJ847kp5aOnN3mWS6WMT0uRtgZIFcp847maD7jt+h6FHsitBf0r6FoFimnimge7VdQN6jVa6OZpkDpmtM61+6utAlpR8o4SEmly2Qb5uckr5N3DSCyMBd3YvSF8MkO+uHyfTaR18fYO4w6O6Evt7sn16PFJxi1zJDw78ZBn7vQTzZ8cPaPSQrfepiIUT2RlqYu5GBmLn0JZ47phH/vbXpUQAAAgAElEQVRHBzg+mVKZLhs4Qi/m1XHl9viWPBb02MlIF1ovsyPSU2i+EWbTBaKZovLBAYI7lDAbgl7TA30mVSDideCwLcjCK2/cwu4hL3/z6FmkGaFX02wDg6PsiHh44MmaaNxI7Uyagt59dK96vuwkorfNNTBa6GYbpY7pgq61ap1bg9D7oiemLy19MHmVpF2J72jAhccfxiY0rswsPx3PlpujggU8Ybwh9Z6lVPcEL5YpMj1xFisa2ZveCkD0ue80f8GVp9Tt1hep2/Du5UfoWgVyceY0FSHuHfaxf4ufS7EsRVdkQ0fopYKKij2epZaL320nixNKvd0UzTuHqt0TJhN67rkQqq/LxcdU2f/g9dWXzCTzDA3U956xWAS//vI9HJtMMlEOKCtnI7dkuFb0IKPsjvDmg9t4/HyMC3P6/6OuBdWBNmtAHwu6ipijZWddyqJBwK2ipGYROs4WrXNrsAZVx4PsXANBT0wwZ43gtFkIex34giq/emp6+ZG1uzBH2hoEixV3UPXn0LrYoOt7p2bYrtstgzfcxSk5jv3yj5q/4OrTqk+2IQjhPctPXczFAcnVYo2gj6oP0qg2sKH7uVQKalPU61saoRtZLpZipne/X3qalG2hP85kne3yEhVpV4pLIvQRf32rAoDX3bqVLX4Xj17R03xXuLHfF+i1EdIzyBtvG8ci4MtP6VG606dabpsReg/Q+7hMl5x1GS4GKtPAobrN1aKX5ls8bRpz6bgi6jKrGFv0qaxpkJrkqhZhNOBCCEE4orzvudnlC7q3FCPrUPnZQq+kFF20JL5zfIYbXarIxz64i7OeFzKWOgqVJqmRV56CsReCxaoGVod3Lz91US/7v5B1MehzEvQ42D+mBP1Kyav6uWxQ8SgXc2hS4Gu0KepxkJUuhCwrUe02pTzk48QsC91CryZqqkMNHx3qBH06mWd4UYQO4LBZ+KU7tvNkVH9sE2e6GEGUxTfEloCLl18/xFeemlioCfGPL8wQXgP6V9CN1rkFe10OuoG/WaaB0Qu9Q0H3De0AoLJ4IySriooulYOMBtTG7EBACfF8bHlCnC9VCMo4RZdeQenwkMfZtQZd5YrG90/N8pJwSk2u8Y+RGX0xbpmndPnpBi8owtSzsPWFHJ9McuOHHuac1POUl5O6qFeJnk472DusNg/HAi78LhvnsnpBzga1XbRiTg2IbpD62vMWuvrG5ZS2cAzXbYyO3KTSEKGasljRJHPpYsMIHdTV0wz6B8Qm9tGNfSubTwVnbz64jelkge+f0m3UwFbTcukJTVrnGgTcdhJlR1PLxeENL3lNI0KBIHHpRSw+yPXLrtO5AKNBdZIIt7JxUvHllf/PpgoMiQSad7h6X8oawNmlBl1PXZwnmS+z3xmD4HawWAns+2kA5p5v4KPPPK8iy7HbeOjoVYpljW9N6tkcy0ld1DeYjsdtXDc8AKj9jf2jfk4k9Q/hdSjoUsq2Q7q1Up4C9rppRQYBw0OH3qQu6hvoE6UBAm7VaXQyUSPoFquK0gPbwan+7tFMgYomGfYvPVcAtobcTEtD0K9hMz56Fj4yAlePrPw91pBicoaKFDj9Kri6d/8IYa9D5aSDGh5vWi49wJhW1MJymS/b1WV9TXpeRbdcXAOdRegDLhtTMoxjcfm/HrGfyA0wpkfouNR75pfZoGsulWeQBBbfgqBnbUFc5e4I+ndPzmC3CobLV6tzJW+8fg8ntXG0cw1aptZsiD78vLr8/sp5XQiWszGqWy5Xim72Di94zftH/fxkXo9s12Gmy6OnZrnjj79dL5KLkKUcRdFYHP0um9q/gR5F6Or/5Fzex2jAxWjAzZV4vv45r/k4vOUL1W+NKtHhgcYR+tagmxmpnxPXEqFffkI1DVvcxneDUEnNMs8AAY/6OzlsFl7/wq18+/g00XRBRejZ6DUNg78W+lfQ9QHRKeluaLkEPXZiJaPj4kKUVEzHSEsXfs/SHhyNsFgEUesg7vyiqEX/lJ6ohKsRujGjtJSJNc5bb0J8fg6nKGMPLJRx5x0hfOXu9As/dGKG23eGsSYuVgV9LODiqO0Ag7FnlvroV54BT4QzxRDnZjPctj3ImZSVsiu8vNRF3XKZlwNcVyPoN476ubqOy/8vXzzPfxVf4Mxkiw/Ucp6SaFyYZrNakHb99+uFoOse96mMj7Ggm7Ggq35TFFT++dit1W8XV4kuZtDnoGzzUrBcY7WoUZ06c2zl77GGyMwsMTmgtw9RvPngNkoVydeeuaIidFgzH72PBV1ZLik8TbNcUtVhvQsnVSkT76yPSw0J2xADi8v/q0VF/oUIXfct3ZU0c+nON8MyUaPsf6x6X9kZxi8Ty/pgaMTEfJZT02levcel7KbQLkBZH/NDd+CUOVVAVMvVp1V0fkz9zn/8hpuxWgTTtrFlR+gVYSODa0mEHkX3eNdhx8XQxLd5p+3fSF1+rulzRDlPydJYHAGEU/99e2W5CAsnkvZqhH41nmt5rCyuEl2MEIKtITdxa/jaInRjoMbMiZW/xxpiyUaJykBdW5Abtgxwy7Yg/3T4MtJIXVwj26V/BT2fRBM28jiI+Bp76I1GgVWycb3TYueCnnEOE6jM11k3JK6Qc48AYiFCt9oo27z4RZZLsc4js0JcRUTeyGj1Ps0dJkSKZP7amgEdOqFE+RUjeraPHqEDOPeoWZLZU4/WLCatoqyx23j4+Slu2RZk3xY/L94d5lhhaHmpi9koWWsAv8tel/983YiPssVJ0eJZn0Mu0upDJhlr7iWLSoFKC0G3ugxB743lIj1DRHMaY0E3W4NuMsVKy2Ol2pirwblisDXoVhuj1xSh620IZk9syJRUaz5KlIEl+vCWg9s4NZ3meFZPd16jatH+FfRCkpLNC4iGlovKNFgaoZNP6BF6m9a5tT/Ko/eKTtcc6MmrJOzK8zayXACkK0hAZLgUa9C2twkV/QRyBBYEXfiG8Ik88cS1pfV998QMOyIexqW+9hpB37d3N6e0reRO13RenDwKUiMaPMBPJhK86iZlA73yxi08m40sL3UxGyOOj73DvrrCL5fdyu5BLwmLf11aLrac+hDMxZu3XrC2EXS7W21G9sZymaboVlkYowFXNaBo5flPp/KEF1WJLmY85FbFRekVCroxkNq3RWWhreHm4UpxFmJEpR+/21Z3/8/dMorLbuEfTugVucm1yXTpY0FPUbDqrXMbbIr63XZyRoReU7EnCgkSy4zQS15daGt9s+QEc5YIXocVv2vhP9/qCeInw6XoMjZNDNuhJsvF5lO77KnYyqOlXLHCY2ej3LNvGGGkG4Z2VB9/wXiAx+WNDEwfXvDR9Q3Rb8XVpeWrblIfZq+8aYQLUv9g6zR1MTfPdNlbzXCpZf+on5mKf11uiroKyvsvpZrbQVatgLQ2F3SHxxD0Xlgu02T0moWxoLsaUFxd7KPXMJMsNMxBr2Vr0M2lUgC50mpRYyC10Z1zo9kulRKucpK48C/p8+R32XnNzaN87dmo6udvRuhdJp8ka/HisFrwOW1LHm4WoVsLiY7midYiAkrcNOM/UdMgqRcVBd110afFHWTQll9WhG7PzlLGCu6FQhGnX4l7NrHyBl3/fm6OQlnjnn3DSoS9Q9U0NgCPw8Yl/4twaNkFH/3q0xDYzkOnS+wd9rFnSH1ojgbc2If0Jl0dpi6WM1FmK946/9xg/6ifybKXSgvRXAs0TTJQVoIus82zlWxaAWlr7EcDOD36HkGP8tDjVpV2OxZQlgvA1cWZLjXMpPJN/XOD8ZCHGRlClPMrG3ZuCPhNr9O/32Abo7r9l7WHG/Z5+ukbhkkXyhTcW0wPvesUkmRwE/Y6Gv7x68fQLZxU9lKKpPTW7WK3wxZU1aLVYdGZWdBKXCwFGQ0sOklcQcLWHJeXIejOQpS0NQSWhf8ud1BdUhdaXPa34zvHZ/A4rNyxKwzz5+vslio77gJAMya+X3ma4pZbeeJCrGq3GOw78EIAkldPdfTztfQc89LH3pFGgj5ATPopp9eXoMeyRQZRYuYszi80vVqEXRahhaB7vOqDU3a7QZdWgfQMc3oR0EjAydCAE5tFtLRcZpIFRtpF6HW56Cu4Mpw9oaZbbT2oBm/MbrAIXbf/Co5Qw4f3DKnMpYR92Mxy6ToFNaSikd0CNb1cYOGyV9NwVtIUbD6slvadFg0GAmEy0kkxpgu67p+dygcWMlwMXIFle+i+cpSso77QyRtS9kZ5hf1cpJQcOjHD3XsHVfHL/IWGgn797l2c1raSO/2oOqDjFzlu2UtFk1W7xeAVt+wlKgeYOt88+6NmAdgKceYZYO/QUkG/cdRPDD+2XHRdbZ5NJfIMCpUuGhYpJuaXimS+VMFJEezNBd3vcZGVTsr5Lgt6NgaywmTZz6DPidNmxWoRjPhdTSP0iiaZTTfu41LL1mCtoK8g02X2JET2qoHUQ/s2YISuzrWSM9Lw4d2DPoSAaTG4ZtWi/Svo+SRxzdUwZRFUC928RRdbI0IvphBIyvalnm4rQl4nUzK8YLnon84ncv6FDBcDVwCPlmYqmW8a3dX9GqUKQa2m7N9Yf1iJqbbCtL6T0ymuJvLKbqmU1AGopyzW8sLtIX6s7cdx5QmYeBKAh+fHGQu4uHlrfQOzvcMDTFnHKM12YLkUUlhkmbTFX7UEahkacJKzh7DK9dXPZTYWwyeUMAZJMzG/9IM5XSjjpISlhaAbll8x1+XfTd+wvFjyM1Zz7I0FXU099Fim2LJK1GDE7yImrjFC1wdSM3yjEnhNW/77rBV6hF7xNBZ0t8PK1qCbi+WgsqR6OZGqCf0r6IUk82Ung03SsIQQ2J2Lijv0sv+Ko7NOiwZhr4NJGUYYB7ku7JNauGGE7qxksKA1jO4WE80UGRQJNM9Q/fpdQcpYECtM6/veSfVB8Ip9w2rCitQaRui7B70ctR3AXsnC4c8iEfzjRIhX3rSloZUlw7sJ5S+TyLaZd6pXiToGBrE0uBoSQlT7vq+nTJfk3MKldLMIPZ0v46SIxdG8OC3oUWmz5VyXI3S9LP9s1ltn940G3FxtYrkYgy2aVYkaWC0CS0C/KluuoJfyytYb2sdPJuLIoX2qc2OiQZfS9YpxHHoGmz5lz5CPE1l9f2QNNkb7U9ClhEKKuXLzCB3A53FRFI4Fy8VonetavqBPEcGR1S9D9aKiGANLI3S3Kp/2ke3IR59LqrJ/MVDvV2OxkBID2PIrK/9/+tI8OyMedZkdO6/ubCDoFosgN/YS9c3ph0kP7CFWdvLKRf65QWTbPsZElEePXWy9AP2DaCA03PQpwUGVPbSefPSsXuQlfSPNBV2P0K0tBN3Yw6l023LRG3OdzHjq0mXHgm6mEnk0bal9ZVSJtovQASKhEBnhXb6gR0+D1Lho2cYv/L8/4vGMfvzMHG/9uvVEZpYKFuy+5n2e9gz5eDapW4hrkLrYn4JeyoFWJtZG0ANuO3nhXhKh415ZhO7Oz6pNqeQVskZR0ZJNUfXenfro8dgMDlGpK/s3SFsDOIsr67h49HKCW7fpvTmqKYs7Gz53z67dnNZUSfMxy15CHjt37Gx8UI/sugmAI0dbN1/KJpRIG6LdiOFRtdk8M7l+8pVLCfWhLYb2ERYpLjewXFLZAk5RxuZY2jrXwOi42PWpRbrlcr4wUGdljQVdlCqSuQaDxY2ionYeOsDWoMp0WbaHrleInkb9n/7blB7FbiBBlxm1ie/3NP/g2zPs5XxZP6/WYGO0PwVd91zTuBlssikKei46riWCbnN31pjLwGW3ErMMYkFlGKiiImNS0VLLBWC4w9TFbEwdFK6asv/qY7YQ7tLy08emEnmmknluqRV0q1ONJmvAC7cF+bG2H4BHElu5d/8INmvjQ8cS2Q3A7IXjLfcIZqeVIIxsaS7o28a3AzA9tXbtSBejGVcLw/txUWQmtvQKKaMPiLY720To0tl9nzU1TcXhp4Cj7upwIRd96cbodAdVogbjITdXtADacgV95jgIKyeL6ors4bM5pH/rhsp0qaRnmJOqsrkZe4Z8TEs92DEtly6h93FJSk/D1rkG1Tam+kklc+rkbHVJ1YyMU7cOklchcYVZEcHvsuFdnAOvd1zc4690JOhG2b8/slTQC44QvsryG3Qduax+z4UI/bwqKLI0Phxu3Rbk+9oLAPhh4bol2S116AOjR7Wr/OB0c+97fk79XuNbtzZ9zo5tStATc+un/7YtO4OGqE5qys4vLf/P53RBd7WI0D361KJuj6FLT5N3Ko+33nLRq0UbbIzOdFAlamCkLmqJ5UboJyC8m4sJ1X5gOlkgE7huQ2W6VNJzxOTSsv9a9gz5KGJXw2hMy6VL6K1zmzXmMlBTixYEvZBWQufwNc4zbUW1/D9xGVJXuaKFGWuQvWFE6Du9pY489HLSKPtfKqIVV5jgChp0HbmcwG4V3KhPB2qWsmgQ8jo4E/opfrrwCS7Zd/Gy65pvCuEOIj0RrrfPVFvrNiIdn0GTgm0tInSH20sOF/lrKJ7qNs5ClKwtoPKoAbLz5Ir1VyI5XdAdLQR9wGkjhwtrufuCnrIbVaI1WS66uF9pIOjTHVSJGowH3czKEJbMzPLSSWdPwtANTMznGA+ptZxhG8yeUjblRiAzRwx/S0Ef9DkIuO3ErENmhN419Na5adnacgl61NQiqQt6URd078DyBb3i04Vp8iho5cZFRVAV9HF3kUuxbHsxNtISfUs3DzVPhABpMvnljTE7cnmeG0f9Kv9cStVfo4WgA9y6PcQFOcrLrx/CZV86tKEWEd7NLZ4Y3zk+rcbTNaCYnCNl8WGzty7gytpDyHWyKZovVQhUYioC1lPXQiK1JHWxkFPfu9zepu8lhKBk9WArd7lvdmqKeRHCahF1WStBjx233bowLLqG2Q6qRA1UhB7EohUh1+GGfLmgunAO7+fyfJbbtofYt2WAf08NQ6WwsCm/zrHm5piT/pZFh0II9gx5uSrDa1It2qeC3rp1roEqLnJWN6aKmXmS0o3f29nBXYt9YIgitmqu9ql8gNFGEbruz486CmSLlbZtdG25WUrY6sr+DSzeCFYhScQ6j2ArmuTZiZoN0dy82nNokINeywu3q+e3tFsMwnvYJieZz5Z49GRjMZbZGHlb+72KijuCtzyvhgf0iIf+4W957I/va/vhOp3MMyQSVNwLgh5maaZLIa8EvZWHDqDZvdi1zgvMOiI9w7QMMDLgrCuOE0J1/WxULTrdQZWowWjAvfxRdNEzICtUItczGc8zHnLz8huGeGROf5/ZDbAxWi5iKyaJydYROijb5VwxaG6Kdg3dcslbvQ37uBgYmQZG+XUlGyfJ8hpzGajioghcUTM4T+X8jDWK0B0+EBYG7SpSauejuwpRUtYQNMj5tg2oqD3dwMdtxpmZNJliZWFDtEXKYi0/94Ixfu2ndnco6Ltx5ybZF7Hxu185yrnZ+kyOfKmCqzRPxdVe0G2+IcIixfHJVPufuwLuf/wiHPsXXlp8jGi0db77VEKlkOIbaRmhF/O6jWJrJ+geHLIIlWtrgVylkIJShivlxsHEWIPJRZpeJdpJyiKoCT0lt243dSro+sbnnGc3ZU0yHvLw8uuHOF7W94VW0qSrmIG/vw+O/uPyX7sS9DTbaBvLBWDPsI9zhYAKlPKrWxTXn4KuZ7k4PIGGxS8G1Z7o1U3RBCm5vOEWBhGfg0kZqnZunJThpRkuoITZFSBkUc9r56P7SjFyjsabtM6A3qBrGYJ+9LLKiqnbEIW2gh72Ovjvr9mP29HabgEgojZGP/vaYaxC8I7PPslcTYR9bjZDkDQWb+OKu1o84S2ERZLjk90/MR49OcMHH3yeAza1eTV5sXUPmqlEjiERxx7YovYKEAxZ00si9FJe/97WRiQdekVytzZG9aKi8wVfw/2bRpOLonqVaCcpiwbWoC7Eneaiz54EYeEC6nXbwm4O7ggjHF5ijtGVbYx++w/g0mNw9tDyX7sS9LL/qPS3zHIBFaFPSv3YXmXbpU8FXUVzTm/rfHK/HqEL/YQS1U6LnfdCNwh5VC46QMXqZL5RUZGBK8AASshbReilikZQm6fgGmr4uCeg7i8mO/eYn7kcx++ysTOi+7ttctBXRFjZN6OVK3zmHbczk8rzq58/XN08PDObJijSuPyNf69aXIFhBkWSE10W9GNXk7z7/qe5adjFLqEizfhk65YFsfkoLlHCHRoFixXhDjLuzC7JRS8X9O/trSN0y+JK5WtFLyo6k/U2vDocDbiZTRcolhf2NRaqRDuL0KFmctZyIvTQLi4n1c8dD3lw2Cy8dM8gx8tbkctNXbzwQ3jiU+rrxOXlvXal6FWiMfwMuJpf9QO6h64L+ipvjPanoGdjZISH0EDzLANYSFu0lrOgaVgLSZLSu6IIPey1M6ULetalioqWlP0buIJYC0m2+F0tBT2ablz2b+AL65WUy2gxe/RynFu2BRfK7ecvKAuhRRHMstFTF4md49ZtQf7yrS/kJxNxfusfn6GiSc5MpwiRxteiSrSKZxAHZaZmu7cxOpXI858+9yQDLjt///NBhKYsj9zshZavy0SVgLlC+ga4J8KoPbskQi8XO4vQra4uD7nQi4qulAMNN+THgi6kXBBxgNlU69FzjdgSCRKXXrRkhxH6zAkY2sfEfBYhFrJvXn7DEEeLYzB3eunc2mYU0vDgu9Wez/6fh/gqtQ7QBT3vCDVsVVHL9rCHWYueCWZG6F0gPcUcoYaTimqp67hYzmEvJUkLb9ssjkaE9QZdAHGbEqotjTx0UJku+Tjbw56Wgj6Xyqmy/wYZLgADYeVlyg6HQOSKFU5OpxbsFmibsrgi3EHlMesDo1950xY+9HM38q1j0/zR149xcTqKRxSw+dpbLnjViZGMdicXPV0o858+9ySpfIm/f8ftDGYXRubJeOtor1olavx/eCJELEstF60q6K0jdLtblYhr3Sr/1y2XGRls7KFX+6IvrHclEbqRi16Y72DTr1xUx8HQDVyO5RgZcKnsKuDl1w1xShtHaKWOe+jz7Q+rrKzXfVJ1bExe7d4eRCv0c6zsal+jYrNa8IS3qnoFU9C7QGqaSS3YkaDnaoZcOMsp8rbldVo0CHvtVctlVkSIeB3NPxhcAcgn2Bb2tPTQ47FpbELDHmzcN8XqcJHGjaXDBl3PXU1Q0WTvBR0gvLtuYPQ77trFf757F5977AJPn9Dvd3dQwOVVVyf2fLR9w682lCsa7/3S05ycTvHX//E2lYc//TxYbMzZtuDKtD75tJSeTWTkoHsiBGWKWKZIprAgKlpJj4DbROgOfchFLrv84rCGpKfRLHYSeBteHVarRWsyXWb0CH1oOYKut9GtJDoQ9Ng50MowvJ+J+Ww1Bx1ge8Sjiougs0yX89+HJ/8/uPPXYcdLIbANZAVSq5BNovdxsTTINmvEzuGg6kxpWi7XjpaaYkoLEG6Rgw6qhW5O6AdYPolLyyy7da5BbYR+RQs3989BRbD5BNvDnpZtdI1LfHewefFNUgSwFTrLBz5ySW2IVjNcysWmbXOvmfCeJQOj/+/X7Oe+A1vwabof3qQNaR1GeqBIcT56bdbEp75/jkMnZ/mj1x7gp2/Qo+yZYxC5jpRnO8HiFJUGzasMLFld0I1RgJ4wXr1StzZKl8ZM1TYeujGGLpvq0v5AepqsY5C6weQ1GFZHbfn/dFJViRpRcyeMhzzMEMKS6cByMYR6UVGRwY4bbqUiBeXJ51u/j2G1hHfDvR9U9wVVJfGq2C6ZOZKWQMs+LrXsGfYyUQmjrXJf9P4TdCkRqSlmZHvLRQiBtOvesb7BU3b4V/RjA247EwxTETaOl7Y0znAx0CP07RE3Ujau3gMoxNWafIPNy+PT1gCuYoeCPhFnPOReaCkcvwTI3kXoiwZGWyyCP3/LrfzSAb0bnaeTCF1ZLmGR5PzctVkTRy7HuW7Yx9vu3L5w58wxGLkRGRhnTMw17G8OaiCIMx9Fw7qwbk8EZ2kekPWvK+sZPW0idLdXj9AzXYrQU1MkrGEcNkvDY9/jsBH02Ossl5lU51WiBipCD+LMz7bvZz57EhCUQnuYTOTYFq7fq7lr/zgX5BbmL/6k9fs88kGIX4bXfnJhv6cq6KuwMZqZY572GS4Ge4Z8XJFhyvOrtGmr03+Cnk8gKnlmZJBIiz4uBsJptLrU26I6l9dp0cBqEWjuCP9r3/3cn7uzcQ66gSsApSw7Amq3vJmPXkkqT7RVhJ6zB3GXO2vQdeRSfCE6h95kuBjoqYuLB0a77FZ+5Rb9b96J5aL3nh4UKc7PXVsRzkyqUL+vUUipD7XhG3EM7mBIJLgw3bh7ZSxTJCznyTvCYLFW12+pFPFQqEbohXIFu2YIeusI3etTx1ox060IfYY5gowFXE3TdUcD7rpq0Zlk51WiBm6HlbR9CKusVPOzmzJ7AkI7mMpa0CRLIvSX7I5wlnFEq66L5x6Fw5+BF/8m7HjJwv1+PdBZjUyX7BzRDoqKDPYOq9RFS2pyVSdu9Z+gp42NoVBbywXAWhV05XWJZXZarCXsdXA0EyaR1xpXiRroBTXbvMoTbuqjpw3Ptnk2SMkZYqCDBl2zqQJX4jleWCfoneWgrwg9dZHJBpGXPtyiowjd4QG7lx2uDOfnrs1ymU3m671io6Bl+EYCW/QukZcbb85NJdXouZK7po+NbgeN2tPV/8N0voxT6F5/mwjdEx6lIO1YYqdX8Ns0IK2sxlZXh1sXTS5aSYQOoPk6LC6aPQlD+6upneOh+gjdZbeSC15PqDCxcGVTSzYGD75XWXj3/I/6x+wu8G2BeJve+90gM8dMZYBAhxlwu4d8TMowtkp2ZQO1V0j/Cbpe7DBD+01RqEkd0yP05bbOrSXsdfD8VRVtNezjYqAL+qA1j9tubVo0YzXK/lsM3Ci7IgRlom0UYBQULYnQbS4Y6KD6c7mM3KhJXWQAACAASURBVKw6Ej7y+wsfTAZZ3SLqJEIHCO3kZRxhcnZl05lAWSaz6UL9VJ4Z3bcduRHfsPoASs+ca/DqhbL/ug9XXdBv8JeqEXpKn1ZUsTgbVvfWEhrw8qzchXvmmRX+VjWUi5CNcqnYYOxhDaMBd1XQNU0ykyow0mGVaC22gH7VmG5R1FYpqZTEoRuYiKmfuS20ND12YPsLsKIxde7Z+ge0CvzzO9WHxus/1Ti1NrhtVSwXmZllRhvA3yYH3cDntJFz63+jVdwY7V9Bl0EiHfR3NjamjHmgNu/KBT3kcVQrIht2WjTQBVrkE7zm5lH++ekrzCSXNk1yF+ZIWcMthUF6IrhEiVymdWn8kctxrBbBgbGaDwcjw6WN8KwImwPe9DnVY/6f31nfUS8XU1WStg4LuF71EcbKl3lj9NPL7ixpMJ8tUarI+mh05jjYvRDYjtD92FKscbQ3nSwwJOLY/DUZR7qg7/YWmIjrEbo+rUiztj/2hgacXPUdIJQ4Rj7feB+lYzLqQ/NCwde8/gF1XCbzZdKFcrVKtN3ouUa4wsrukK36lcTOg1aq5qBbRONU3r03HQTg7PNP1D9w6KNw5tvwmj+Dbbc3/hmBbb23XMpFRCHZtnXuYuwhNcxjNVMX2wq6EGKbEOKQEOK4EOJ5IcRv6feHhRCPCCFO67fLb1HYC/Tiirg1jLeDMnWnVwl6RRd05wo6LRpEaiye1hG6Lqr5OO+7dy9lTfI331t6qe8tzZNxtM4EsfqUBZBok6d9dCLOvi0D9aX7vUpZNBi5Ce77M+WB/uATC/dno+BZxt95zz08t/3/4pfEwyR/8m8rWkrDMWvTz8PwftUH3j+GhgVbkx7WU3FVE1AtKoKqoO9w5esidBdFpK29SAohuOHgPbgo8s3vfHtFv1cVPVKe0gItI/TavujG32QlEXpgSIlVNtpCrIwK0OF9TMzn2OJ3Ney5vu26myljJXGxJkI/9hD84BNc3vUmPjRxO2dmmmyIB7epTK1eDps2yv4JtOy0uBjf8E4A5CpmunQSoZeB/yKl3A+8GHi3EOJG4APAd6SU1wHf0b9fe1LTFISLYDDcso+LgVvPBRZ6pOEa6CCVrgkhjxJ0IdqM8zJsnXyCHREvb7xtK/c/fqmugq9c0Qho8xRdrddjG1B52q0adGma5MjlRRuiUuqC3oOUxVpu+xW4+c3w6J/A+R+o+7KxzlIWa4i9+AMc17bh+cZ7YQXtdI0xa9VoVMpqhgsAVjsZ5xD+4tSS/uYAyflZHKKCtdae0vcAxhxZ4tkSqXxJReii1L6Pi84NL7oHgFOHv1uXy75sUgt7R60i9IVc9Hz1bzK0ggh9NBIkKgfIxVoJuho7x+D1XJ7PMh5uXI0sbE6izm245k8xly7w7e89Sv7L7+Ko3MO9x3+Oz//4Eg8dbXIlENwOlWJr6+dayRh9XAaWJegjY9spSwuZudUbhN1W0KWUk1LKp/WvU8BxYCvwWuDz+tM+D7yuV4v80IPP8Vv/2KHPmJ4iKkJsCzfvRV2L1+tDkwJbbhZNCrz+lUfoRqve4QEn9iYj2oCaCF1tZr73nuvQNMnfPLoQpccyRYZEAs3Tujzepc8azcebt9A9H82QypfrC4oyc2o4di8jdFCfbj/352pT66u/qvz0XKxz/1xnx0iY3yq9B0sxBQ+9Z9mZA0YBTdVyycyqK4XhG6vPKfrGGRdzXGiQ7543JvTUeuiuIAgLw1b1/In5HOlCCRfFtjnoVQJbKXq2cH35BJ/90TX0BdevTGfl6kTo4yE3MzJEuVVx0exxJbgOb8Mc9Fq0of3slpe556MPses7v05WOvjWTR/ns//5bgZ9DmZTSy1JAAJ66mIHtks0XSCeXd7sAKCuMddyLJc9IwGmCZGdXYVNW51leehCiJ3AC4HHgREp5SQo0Qc6aMyxMhK5EocvdNhMPzXFpBZkW7izEyrgcZBBHeQp3AQ7LBxohCHoLXPQYUHQc2qjclvYwy++aJwvPXGp2q96NpklTBIx0PrP6g3pDbpSzQXdKChaUiEKvRd0AKev3k/PzHWW4VLD1qCb85btHNr2bjj1TTj898t6/RLLZVrfEK0RdGtoO1vFHOdmlwp6JaFHgLWCbrGAO0RIqP2LifmcvilawmLvPOp17LiDlzrP86nvn2tZDatpkr/93lkOX2iQWpmeQSKYI9By/2bE70IIVf5fnSW6giwXo/zfkm5RXDR7Eob2USxrTCXzDTdEDQZ33cJ2ywxfG/47dltnCb79S/zem+/hrr2DDA+4qlcTSwhuU7cdFBe9838f5te+8FTb5y2hpjFXp3nosNB1UYuvL8sFACGED/gq8H4pZceJs0KIdwkhDgshDs+usMHS9rCHyUSurktcMyrJSSYrgZYHTy3VuaKw4sZcBqGqoLc5mW0usDqqETrAu1+xF02TfPKQitITsRlV9h9oXPZvMKA36KqkmvdzOToRx+e0sWfIt3Dnago6wJYDcN+fKj89fnHZEbrNamFb2MNXrT8Le+6Bh/8fNb6sQ2aSBXxOGx6HnqVg5D3XCLpneCdbiHFhdmmamXVxlWj1RREGNKNaNFv10C2dRugA47czXJ7EkY/y6R80TpuUUvL7Dz7Hx75xgvc/cGTpuZCaImsL4HK6WoqO3WpheMCpLJdUnpDHvqwqUQO/y868NaSKixpRKesZLvu4Gs8hG+Sg161r9EYsSPYkfox49R9j2XV39bERv7N6hbWEQGeCni2WOTqR4PHzMS5Fl1nPoAv63DIj9BG/kxkRwZ5ZvZm4HQm6EMKOEvP7pZT/rN89LYQY1R8fBRqGiFLKT0spD0opDw4NtW+X2ojtES9ai4rKOtLTzMjgkoq0ZvhrGnSttHWuQdjTYYQuhLpcrxH0bWEPbzq4jQeevMzVeI5MVPf0Q0uHQ9etPxCmKK3Vy8JGHLkc5+atgboJNpz/HgirGg69Wtz2djjwi+rrZXroALsHvZyP5VS1oN0N//yfVbpeB8wuzreeeV71ifEtHJOO8A5sQiM6VS8O+VIFd1GPihfXBHgiOIpxPA4rl2M50oUyLlFCLCNCZ1xlcLxzd4zP/uhCXe94UGL+R18/zv2PX+KefcNMzOf4hycWCVh6mnlLqH0wgcp0MSL05fRBX0zeNYKvFG08E3T+ghovN7SvumG8OAe9ji03q9sXvBXueFfdQ8MDrrr9pTqcPhUctLFcfjKRqLZ1ePDIMrNOMrNUhJUkXvzuztIWQW165z2jDBSWOX/1Gugky0UAnwGOSyn/Z81DDwFv179+O/Bg95en2K6L88V2vTwKKaylDNMy1DIaqEVF6Iage9v2Om6FkeUy1qqPi4Fe/l/Le+7Zi0Ty14fOUIirS1kjAm+GzWYlLvxYco0rHPOlCscnk9y6vcZuufRjeOYLcOevde71dgMh4Of/Am56A+y9d9kv3xnxciGaQfNtgV/4SzW/9Yf/s/0LUZZLnbUwfUxluNSiX77nF7XRndFTFiuiwShATwSRjTEecjMxnyWdL+OxlBDL+buO3gIWG28ZnSJfqlSv0gw+8a1T/P2PzvOOl+7kM28/yJ27wvzVd8+QLdZsourtLloWtOmM6dWiM6nCiuwWg8r/396ZBzd6l3n+89Nty5Jl+b7tTt/pdNI5ugPhSEISQgIJLMkSdmDDLEOgmOEomEnB7G5RuwOzDMXOQMEM7CwLpGqAwMAEwjEDOUlISCahk3T6SNKX2227bVk+JNuyZVn67R+/95VkW7IlWZJb6t+nyiVLlqX3lV49et7n932+j7sVK4lkBruMEw+py9bdSVuENcug/i3woUfh9q+vktG2eJ0EZ6PZfXZy0KIfHFQl251tHn764nB+8tdIkIitAZfdmv/ZjLcTB4tKCFAGcsnQrwHeD1wvhHjR+LkF+CJwoxDiOHCjcb0kXHzor/nf9m+sO90n3T40n5KLWUOft7jX9Tpei05fDX91+8W8a19275UkhoXuyv9/z1Xd/Oj5swRH1QFa4187QwcIW+qxRzMfMEfPhYnFJZd2mYZcUXjw4+pU9br/uv52FhunB+78DnRdmfe/9jW5WYipeiy73gHdV8PJR3P638BMNNXinkgoSV3LxcvvVJ/yBkn/wI/NqNFzsZqm1Zr9Wj9EJuhqqDUWRZeoyUPlAqiGmdY9NEy+xLsv7+Kfnj2TXEv5+qPH+fpjJ3jv/h4+947dCCG49+adBGejfOepAfX/CyEYfZkjS11rW04YdBjdomOhhQ1l6GZzkVzpdjgbgMf+F2y5Ftov4+xUBKtF0Lbec3VeAdbVJY0Wr4uEJPtcWV/PuiWXg2em6W9yc/fr+zg5Psfh4TzsFuaCzFjrCxpN6WpSx1QkWJ6F0VxULr+TUgop5V4p5WXGz6+klBNSyrdIKbcZlyX7CqpdmuaA5Rhn1qt9GQs0M/bGnGvhagyd+vBFC7TONRFC8P7X9eXU0GQ6Lq7kT6/bikAwNKQOgGxe6OlE1jDoMjtEzSHP/O4rEHwVbv1bdbpaQWxpUsqlAdMCoKEXwuvXJ6WUBMJpJZfpAYhFUpJFk3qlrW6IjTGVtjg5GlJdotKdYT2jtlEFdJ8rVUMXsXV9XFbRvR+GD/Lx67YgpeRrj57gW0+e4su/eY3/sK+TL7xzT1KGe0VvAzfsauGbvz2pVBuv/hskYjywcPn65T5USTBqLFQW0vZv4vIbWvTgihLGb/67en1v+TIIwdDUPO31LmxrKb/WwNzG7HX0HlVyyZJ1Syl58ewU+3p83LKnHYfVwgMv5FF2mQsSEoUFdF9rHwCBoRz93jdIRXSKioZ+2sUkwxPreJYYXaJWb1tOGnRQLbpmyWVxgwE9LzKUXEB92O7a302zmCaKA5zruz/O2xuoXcr82vzb4VF6G2tVJjb+Kjz5Zdjzbth+04Z3odz0GQH9lBnQPe2qLXydppLZ6BLzsXgqeGVYEAXAUcui00+nGF/m7Kja/qeTQ7mXUeOHRIwtXkl4YYnh6XmcLOaXoYOqoy/O0r10hruu6uH+fx/k8788xq2XtPOlO/auOnP89E07mI0u8c3fnoJjD7LkbuMFuXVt22aD9JLgRjL0+mZVopoeTyt3DDwFh+6H138MmpTX+dDUfM5nzJkwtzFrHd3Xrb5AspQ1zk7OE5xd5PKeBupr7Vy3s5mfHxphKZ5jM1IkmLfCxaStW5nUhUYH8v7fQqiIgE5DH1YSRNc7bTGaC5xmy20OCCFYsqqsJl6gdW5BuOqTssWVfPTarbRawszYGnJqy485G/AmVgf0w8NqVf/9V/eqoPfzT4C9Fm4uWXWspLR5XbjsllSG7u1QreXrOP4lNehJyaIxlLh556r7yvpuulZIF1WGHsZWn8Hzxljc7atRweZEYAanzEOHbmKWoIae42PXb8XtsHHDrhb+7j2XZcxsd7V7ue3SDn709DHk8YcZ73orEgududTQ0+5TiAbdpLG9i4QUzJvdovEY/PLTqpz3pj9P3u/sZCTnNa1MrJuhJ210M8cHs35+eY9a/3jXvk7GZ6I8fTJHb6C5IMFEfm3/Jp1dPSxKKwsT5WkuqoyAbjj32UIDay5myPA5otJOY1N+apq4TWUPCVfhPi55Y2boGfanrd7Fm9oT1DasvSBqEq9pxMvsqlFc33lqALfDyn+8qhsOfhcGfw83fX5N98bzGYtFJBdGAZWhw7oTa1Z1iQaOgq83Y8nJ7u+l0zKROgsAxkIRGkUIUZel5AJ0OVXNOxaX2AvJ0Bv61WMNPU+L18VTn72e//ufr8zYKm/yqRu38wZ5EBFf4HjjdUAOklmWq7AK6RI16fR7mcCTai569puqmejmL4JDnU0txOIEZqJrK1zWwVy4zapFN6WLWZQuBwenqHVY2d6q3u9rd7Tgcdn4aS5ll6UoRMOMxQsL6E67naClKWn+V2oqI6Ab7ekt8VGCs9llaovTI4ZkMbcuUZOE3bi/q5wZuk9ll7HMUkx/YpLaHBZEgWRQWQinNMGBmQV+/tIId1zRhXcxCA99DvreCPvet+FN30z6m9ypYOs1Xp916ujJpqJkyeWo8pnJgMVoLjqd5h0SCQWUmiPTF6Hx2rfa1TYJEthlATV0IVTZZeg5QOm81ysb9ja6+VDjywSll1+F+oAcJLNAo9uR/KLYSIbudzsYx6+ai8Ij8PgXYdtbYeetyfuYzo65Nvplwm5VAzvGsnWLJpuLMgf0FwanubTLlzzTcdmt3HpJO78+MrpcKZQJQ8Fzbqkur7b/dGacrdTMl0eLXhkBva6VuNVJrxhjcDK7dHFx+hwBctegm0gjm7DmOC+wKKxo/1/G/JRauGzbm9NDmQZds5Oprr3vPTPIYjzBB67ph3+9V2Ua7/hqaZwVy0hfk5uzkxFV/zR9VdbJ0JOT7T0u9ToEj6+un5vUd+Nikcnx1GMuhTN0iZoYHa918RB1ThsOjACRb4YOquwSfDVrKW4VixEujjzLw3I/9/9hhIZa+3LztSxYLCKZyW9EtiiEYMbehHM+AL/+SzU79G1/s+wYO5uLBj0Hmj3O7Bm6y6fWmjJk6POLSrZ7ee/ys+937utkbjHOQ0fX8YAx+juGF90FB/QldxsNS+O51+w3QGUEdIuFJW8vPSKQdboPALNjeWnQTYQR0O0bsM7NmzTHxVWceRpkAvrfmNND2Q2DrjnDz2UhFud7z57hLTtb6A88AscehDffm5oiVMH0N7qJxaVqMqtrBUQOGXoUh82imkKCx9Vg4ZUadBMj24tPDZJISKSUiLksXaKQzNDFvNKiuzDOIAvR9xsNRgzn2J5+8hEssQhy921Abtm5SXu9q+Au0XTmnc10LJ6GIw/AGz6VGmxiMJQcbLGxfodWryt5prUKIVTZJYN08dDQNEsJmayfm+zv89NR71q/7DJXmI9LOhZfN61MMLRGMlosKiOgA7amLfSKsTWli45Ifl2iJuaQC0ddGTP0NMfFVZx+UtkDdGXxgF6By6cCzcK0yjZ+/tIIwdlFPr4zBA98WDWuXPOJomz2ZtPfrL58TwfnlGa5riWHGrqS5wkhVLkFspZczHpsSyLASGie6UgMX9z40s1UQ3fVq47byARdDTU4yW1aUUY6LgdEsuyyLkcfhJoG3nbrHXhctrzKGm/a3sybtxfWuZ1OvK4NO0uqLJrhGBuamsduFRtS04Aql2XN0CFrc9HBTD5GqLOU2y7r5Injwez6dljh41JY02Fr10U4RBxfovSTiyomoFv9/fRYxhnM1i0am8cZn2XG3kidM78XfqLxch6J78NSzgx2rZLLwJPQfSDnoOBuUKWHWHgcKSXffmqAG5qm2fvbD6mA95/+OWPDRiXS15gW0MGQLq49fX7ZmLXAUbDYoXFr5jsbGbpp0jVqSBaBzCUXIZY1F7mEkaHnW0MHtYbTsju3gL4UVSZlO2/F53Hzw3tex3+7NUsZKQMfvXYrX7lrX/7buBJDYRK58YtqJNwKzk5G6PDVLLedKIBWr4vxtbpF67shtDpDf2Fwir7G2oy9Ie/a10k8IfnFoTXO8Ap0WkzH37UDmrbjs67xxVEkKiag4++nlgVC41myMeNDncjU/LEOCf9WPhj7C7zewgZEF4SpqFlZL52bgLHDOZdbALx+FWiW5oI8c2qSqXOn+Wr8rxAWK7z/AfDk/5qcrzTVOfA4bculizmUXJIKl7GjajReti84l4+Eo04tjAbnkrNEE1an6nLNhNlctNEMHVQdfej59Qc2nHocomHYdTsAuzu8eZ+ZFgP3FXfx9ujneWAmcwlroxp0kxavk3hCMjmXRRTh61HJUVqCJKXk4OD0qnKLyY42DzvbPGs3Gc2Nk7DYCVNbcEBn2w3wZ89BU5YkoohUTkA3BzFMZfGMNjToVm9uUr90TEOugt+wQsiWoZ/5nbrse1POD+WrcxOStYi5IPc/cYh/cn2J2vgMvO8nyiOjihBC0Nfk5rRZevO051Zy8aY1FWWrn6snQPh66LVOcDo4x5jRJZpwt2RfUK5thMikytA3UkMHVWZbmIbJdToLjz6oFgK3vLmw5ykSB7a1Y+u6nG88fpJYhkW/9XzQcyWlRc9d6TI0NU9wNsq+3uyl1Hft6+TFs9OpBGElc0EWHQ2AKHhRtJxUUEDvA8AzP5xxokzCyNJcuUr90rhhdyufunE721rK2AqfLaCfflLNuey8POeHctgsTFFPInSW952+lz4xirjr+6p2XoX0N7lTnZzedqUKyiL/XIjFCS8sqYCwEFan5Stb/lcg6rvpsykt+mhY+bhY1jrLqfVDZJJrdzTzgf2G8qbgDN1YN1mr7BKPwSu/gB1vK/x5ioQQgo9dv5WhqflVC4zzi3GCs9HiBHSjBp9di7560EWqoSi72OG2yzoQAn6azYFxLsi8XX0hlDXhK5DKCei+HiTCkC6uXhidDSoTeW9Ld94P7Xc7+Phbtm3ImCtvrHYVuFeqXE4/AT1X513znrF62Rf5PVeI48ze+o1Nz9xKSV+Tm+GpeaJLcfAYX+AzmcsuyySLyZb/LAuiJr5u2uQ4p8ZnGQsv0G4NYcm0IGpilFxcdivv3mvYAhdSQwdVDnJ61w7oA0+q42bXbYU9R5G5fmcLu9u9/MPjJ5fVuIenTZfFIpRc1s3QzW7RVB394BnVULSjNbulR3t9Dfv7/Pz6SBb5YiTIrE0H9OJjdxFzt9FjyRzQ5yaGiUkrLS35l1w2jZWOizNjSoecR/3cZM446H7S9kl8V95ZrC08L+lvqiUh1YIbZoktSx3dbBdv9jpTCpe1Si4A9d3UJmYJTU9wZiJCswit3V1rBHSkVIuVUHjmbLEo18G1AvrRn6lkoAAL4lJgZumng3P88uXU+5DSoG88Qzf18mPZMnR3k/oSTQvoL5ydZm9Xfco64Vf3qga7FVzR28DxsRmVIKxkLsiMRc0SqM1B47/ZVE5AB4S/nx4RyOiLvjg9opqKGivIQXCl4+KAMUQ5j/q5ycO+9/CpxY+w4x2fLNLGnb/0N6n3+HQwkkOGntYlGjgGjrpUNpcNox7bQZBDgxN4ZXjtgF7jV9r2hVCq9LMRn/muq9SIvGiGSfeJOBz7hTJXK6eX/Tq89eI2trbU8fePniBhZOlDk6YGfeMZutNmpaHWvo4WvStZclmIxTk6Ek4tiM4G4Llvwe+/DqHlI+F2tXtZSkhOBDK83nNBpoRSuORq+LeZVFRAtzVuoU8EMvuiz4wyLn05mROdN6x0XBx4Up1uF1D7brvkWhJ772JvVxmbozaJ/sY0G91khp55YTSQXnKZOK4cANf7YBr12E4RpCY2hQW5foYOKkvfaIYOKqDLBIxkGIx+5mklpdt9e+GPXwIsFsGfXbeVV8dmeOiYKl8MTc3jsFlozsVOOgdava7sGTos80U/NBRa3lB0+CfqS1cm4JlvLPu3Xe3K8uPoyAqP9NgCLM4wSWHWuZtB4eN5NgHh76NZTHMuuNolzTEfIGRtwmU//0+Lkrjqlwei009C7+vBmv/b8idvrC41y1rU19rxux3K08XZrxwks2TogXAUq0XQ6HbAxMncmrXStOijwph9mqlL1CQZ0CdhycjQC62hQ8p58f4/gmalYaZpm7o8+jPVdLb1xsIfv0S8fW87X3n4Nb726HFu2t2qFC6+mqKtTTV71pgtCup9O/cSkFoQTU7qeul+lSg1boM/3Kc6pw1hQn+TG5fdwrFzM8sfz9Cgjyc8BTcVlZuKytBN6eLSxMCqP7ljEyy4Nt75VlbSM/TwiJKq9eVfP78Q6WusVRm6EEq6mDVDX6CpzoElEVOn47k0j7lbwOpgm3NK1c8hc5eoiRnQ5yeLk6HX+uGOb8Ml71aPc+IhePhzcP97ldf41hvOy+EkNquFj167lcPDYR5/bZyzUxE6i1A/N2nxuBjP5okOqrkoEoTFCC8MTtHbWEtTnRMCr8C5F9W80td/DBZnVFA3sFoEO1o9HDu3IkMvgjFXuamMrx0TwyfCGR4knpCp7rOlRbyJMHF3Br/q85n0QdGnjfp5AQuiFyL9TXU8dcKYZentyNotmmwqmhpQp9v+HAK6xQL1XWyNTHEoukaXqIlh0EVkojg1dFBDSPa8O3V9flr50EyehL43bOyxS8g793Xy1UeO87VHjnN2MsKeS4onUmj1qgw9kZCZs36fGnguQ2c5ODjNG7Yq0zoO3a/sGS65Q72P/W9SZZcDHwGb6kHZ3eHlXw+PKu8esyRnZOijMXfFlFwqMkPvkKPLppfEDIWD1VtpAb1edfslEkqu6PJB6yWbvVUVQX9TLaPhBWV/ukZzUXL0nNmok6u9gzHoogkzQ8+zhm4tsj68xgfdV8GldyVH5Z2POGwWPvLmLRwcnGYqEiuKwsWkxeNkKSGZimTrFlWlsuDZ44zPRJX+PJGAQ/8MF12feg9f/3F1vBz5l+S/7mr3Mh2JqXm1JkaGPhgt3Gmx3FRWQK9pYMnuoWeFSdfEObUQUuPPYTjz+YSrXmWNizMw8ITKvCyV9ZZsFqbSZSBoSBdnRjMOC1HDoZ2qfg65d876ummKB2i1hJS9smMNj32nByw2I6DPq2B+Ab+Pd17ZndSNF0PhYpIaRbf2oIvhM68BsK+nQXVeh4fUF6HJ1hugeRc8/bXkMWMujC4ruxgB/czCBtr+y0xlHXVCkPD10SsCy3zRp8dUQK9vPn8zl4yYjoujL6vVeV0/z5m+JhUoBibmlHQxvrhqFN1SPMHEXFRN5Zk8CTUNqfLIetT3ULsY5M5tINZaEAXDoKsxlaHbNuYsWOm47FbueZP64jQHexcD074hq3TR0wYWOzOjp6mxW9nZ5oGXfggOD+y4JXU/IVQtfewwnHoMQN0Xli+Mzo0jLXamEy4d0EuFrWkLPZblvuhzxkzDpo6+TdqqAjHb/4/9Ql32568/v1BZ5rqYRbo4MbeIlIYGfeJkbvVzE+P0vS54aO0FMTlzMgAADoZJREFUURPDz4XYfEbXwQuNP76mn/vvuZqLO4o3Bcw0WMva/m+xQn0niekzqqEovqBUQbtvA8eKM4VL7oC6NpWlAx6XnW5/TUq6OPgMvPQD4r4+QBQ0IHozqLiAbvH30y3GGQymvkkXp88Rl4LWtgosuYDy5ahtWr+DUZPE7bTR6nWqgJ6luSg1S9QJk6fyG/BhzqkMD+c2g3VZhr65/irnA1aL4OotjUVtxmler/0fSNR3Uzd/Tvmfv/orVc7c+57Vd7Q54cCH4eSj6gwZ2NXm5dhICJ79P/DdW8HhZvCGfwAqo+0fKjCg09CHnSUiwZQJj5gdZUr4sNkr40VPYlrohs6q+nkFdKKdT2xv9XBkJJw1Qzc/+K21qO7AAjJ0IMeA7k/p0DeiQddkxWW3Ul9jX1OLHnK00yGCXNxZD4d+CN7O7KXMK/9YWSg8/XUALmlx8LHwl9XIxq03woceI1ijLG91QC8VhnRRTA8kb3LMBwjbGzdpgzaAK81/XcsV8+aqPj+vjIYJWfyAWJ2hGx/89sQ5QOaXoXs7QRgfj5xLLjpDLzWtXucyhdtKhmmilSn2emfhxCNwyZ3ZF6hrGuCKu+Hwj2HgKe4+9iFutzzFyOWfhru+DzU+QvPK395bUxkK78oL6IZ0sXFxJPliuxcnWHDmkEWdb6QH9AL8Wy509vf7kRKeH5pRWfTKDN0ouTQsGN4d+XjDW+1KDgngzqFhrbZRNRYtzp1XHivVRovHtWaGfiLagEVIeo99S7X6p6tbMnHgI0rp8t1bcC+M8l9if8HjrR9IfgmYMUZn6KXC20lC2OgRY5ydjLAQi+OXkyRyyaLON5xeQKgMsGnbZm9NxXFZtw+H1cKzpyeVwmFVhr6A3+3APn1K3ZDviEGzjp7LsVXjVxLU2YDO0EtIi3ft2aIvhJVaRRy8D9r2rr8u1dALV/0JdB/A8uHH+YP9ymXSxXCFBfTKOI9Ix2oj5umid0opXVxWyRbCBCutqQhUFlDbqNQtun6eNy67lcu6fSqgN3QsG24AabNEJ06qRWdXniMGfd1w9pncSy6gFlGNYSya4qMy9IXlHZ0G8YTk6Qm3SlOXFtbPzk1u+RIAAtjZfm5ZQDczdI9WuZQOa+OWZHPR2LlBLEJWXlORyV3fhxv/arO3omLZ3+/n8HCImLs1w6JoVCkj8lW4mCQz9BxLLgCLszpDLyEtHiexuGQqElv1t4GJOU4v1iOxqPWPPXfk/fi72r28MjqTtAAOzcfwOG0bHnJdLioyoNsa++m1jDM4Ocd0QNVH61sqrKnIpOdASqWhyZv9/X7iCclwvEHVsGOpBbPx8IJhm3siP4WLyfabVUOKJ4exhukNS7qGXjLMbtFM0sXDwyGWsBHzdsNFbyloOPqudi+z0SXOTqk+l/BCrGLa/qESSy4A/n7qmSUYHCMybwT05nWGFmiqkit6G7BaBK/M1dEHqo7u70dKyfhslE53Qt3WWIC9cM8B6PlBbvetTVNZ6Qy9ZCS7RcNRdq6osh4dCeOwWhDv+zHUZh8MvRbpFgC9jW7C85UV0CsyQzdrlImJAWIhdZptqcQaumbDuJ029nTW89ykEUSNhdGpSIxYXLLFasyKLCRDz4dlAV1n6KWi1WP6uWTI0EdC7GjzYG/ZnluZLAM7Wj1YBBw1LADC80vUV4hkESo2oCvpYs3sIInQKAlEbs0fmqrkQL+f3weMgG7U0c1T8m5pKF8KqaHng8MNVmXFqjP00pHyc1mudJFScmQkzJ7OjVkN1Dis9De5kwujoflYxShcoGIDeh8APYxhiYwRsdUr3bDmguRAv5+huNF1a2ToprStNaZ8fvLSoBeCadAFuoZeQlx2K16XjcCKDH14ep7pSIzdHXkqmTKwq927LKBXio8LVGpAd9YRczXSLQI0M12ZTUWaonFlr58ZUUvM4gLDG9/M4Hzzg0p26PSUfkPMgK4z9JLS4l3dXHTEMNXaUwQzsF3tXoam5gkvxAgv6Ay9LMiGfnrFGK1iqjKbijRFo77Wzs62eoKWxuSgC7PkUjNzpvT1cxNT6aJr6CWlxbO6/f/IcAiLgJ1tGw/ou42F0cNDISKLcR3Qy4HdsNFtEdOVN6lIU3QO9Ps5G/OSMBbJA+Go0g9PnSpM4VIIOkMvC61ZMvStLXXUODY+JN5UujxzSvnra5VLGRD+ftrFJE2EKrepSFM0DvT7GUk0EJtWAX18JkqvJw5zgTJm6LqGXg5aPGq2qEybUHV4JMSeItTPQRmANdTaeebUJFA5bf9QwQGdhn6sJLCJhA7oGq7q9zMq/VjnxkBKAjML7HEZQ6RLrXAx0Rl6WWjxulhcSiTb8sdnooyFo+wu0jANIQS72r28eFYNCK+qgC6E+LYQIiCEOJx2m18I8ZAQ4rhxWZiKfyMYNroAwqNLLhc6TXVO4u42bHIRIpMEZqLssI+rP5YrQ6/RNfRy0OJZLl08MqIGee/pLE6GDqqOvhhPAJVjnQu5ZejfBW5ecdtngEeklNuAR4zr5SXdAEkHdA3Q0NYLQDw0TCAcpU+Mqj+UWrJoojP0spAaFq0WRk2FS7EydEjV0aHKMnQp5RPA5IqbbwfuM36/D3hnkbdrfepaU5mQVrlogK5elYm/duI15mNxOhIjyodl5TzJUmFOOXI3lef5LlCSGXo4laH3NtYWVS+eHtAvBB16q5SqBc+4LL8QXIhUlq4zdA2wY9t2AF557VUAmqJD5aufA3QfgA8/Ce2Xlu85L0DMbtExQ5p6eDhc1GHUAFtb6rBblcOiVrmkIYS4RwjxvBDi+fHx8eI+uL9fjZHSp7gaoLWjjwSCwPBpALyRwfKVW0AlGe17y/d8Fyi1Dhsep41AOEpoPsbgZISLi6RwMXHYLFzUXIfTZsFl37gUslwUGtDHhBDtAMZlINsdpZT/KKW8Ukp5ZXNzYYY5Wdl/D1z72eI+pqZysdqZtTXgjQXxMoc9OlneDF1TNpq9TsZnohw16ufFztAB9vX4aKt3Ff1xS0mhy7cPAncDXzQuf1a0LcqHi65TPxqNQdzdRlt0Mm1BVAf0aqTV42IsvJBUuBQ7Qwf4zNt2JUfQVQq5yBZ/APwe2CGEGBJCfBAVyG8UQhwHbjSuazSbjtPfRZuYYqvNsM3VGXpV0uJVzUVHRsK0ep1qMlWRqa+x0+0v04J6kVg3Q5dSvjfLn95S5G3RaDZMjb+TttPPcLEtCEsiabWsqS5MP5fDw8XrEK0GKrdTVKPJgPB20ECY19WNQX0X2CurBqrJjVavi+hSguOBWS4uYkNRpaMDuqa68Kj5rLtjh8urcNGUlfQSSykWRCsVHdA11YU5cHtuXNfPqxizWxSK2/Jf6eiArqkuPB2p37XCpWoxu0V9tXY6KkxaWEp0QNdUF2aGDjpDr2JajAx9T0c9QohN3przBx3QNdWFy5fy+NEZetVS57TR1VDD6y5q3OxNOa+oHF9IjSYXhFBZ+tTAckdOTdXx8KfejN2qc9J0dEDXVB+eDkjEwebY7C3RlJBK8lgpFzqga6qPaz4BC6HN3gqNpuzogK6pPrbftNlboNFsCroApdFoNFWCDugajUZTJeiArtFoNFWCDugajUZTJeiArtFoNFWCDugajUZTJeiArtFoNFWCDugajUZTJQgpZfmeTIhx4EyB/94EBIu4OZWA3ucLA73P1c9G97dXStm83p3KGtA3ghDieSnllZu9HeVE7/OFgd7n6qdc+6tLLhqNRlMl6ICu0Wg0VUIlBfR/3OwN2AT0Pl8Y6H2ufsqyvxVTQ9doNBrN2lRShq7RaDSaNaiIgC6EuFkI8aoQ4oQQ4jObvT2lQAjxbSFEQAhxOO02vxDiISHEceOyYTO3sZgIIbqFEI8JIY4JIY4IIT5h3F7N++wSQvy7EOIlY5//h3F7vxDiWWOffyiEqLpRS0IIqxDiBSHEL4zrVb3PQogBIcTLQogXhRDPG7eV/Ng+7wO6EMIK/D3wNmA38F4hxO7N3aqS8F3g5hW3fQZ4REq5DXjEuF4tLAGfllLuAq4G/tR4X6t5n6PA9VLKS4HLgJuFEFcDfwP8nbHPU8AHN3EbS8UngGNp1y+Efb5OSnlZmlyx5Mf2eR/Qgf3ACSnlKSnlInA/cPsmb1PRkVI+AUyuuPl24D7j9/uAd5Z1o0qIlPKclPKg8fsM6sPeSXXvs5RSzhpX7caPBK4HfmzcXlX7DCCE6AJuBb5lXBdU+T5noeTHdiUE9E7gbNr1IeO2C4FWKeU5UAEQaNnk7SkJQog+YB/wLFW+z0bp4UUgADwEnASmpZRLxl2q8fj+CnAvkDCuN1L9+yyB3wgh/iCEuMe4reTHdiXMFBUZbtPSnCpBCFEH/AT4pJQyrJK36kVKGQcuE0L4gAeAXZnuVt6tKh1CiLcDASnlH4QQ15o3Z7hr1eyzwTVSyhEhRAvwkBDilXI8aSVk6ENAd9r1LmBkk7al3IwJIdoBjMvAJm9PURFC2FHB/HtSyn8xbq7qfTaRUk4Dj6PWD3xCCDO5qrbj+xrgNiHEAKpcej0qY6/mfUZKOWJcBlBf3Pspw7FdCQH9OWCbsSruAO4CHtzkbSoXDwJ3G7/fDfxsE7elqBh11P8HHJNS/m3an6p5n5uNzBwhRA1wA2rt4DHgDuNuVbXPUsrPSim7pJR9qM/uo1LKP6KK91kI4RZCeMzfgZuAw5Th2K6IxiIhxC2ob3Ur8G0p5Rc2eZOKjhDiB8C1KFe2MeBzwE+BHwE9wCBwp5Ry5cJpRSKEeAPwJPAyqdrqX6Lq6NW6z3tRi2FWVDL1Iynl/xRCbEFlr37gBeB9Usro5m1paTBKLn8upXx7Ne+zsW8PGFdtwPellF8QQjRS4mO7IgK6RqPRaNanEkouGo1Go8kBHdA1Go2mStABXaPRaKoEHdA1Go2mStABXaPRaKoEHdA1Go2mStABXaPRaKoEHdA1Go2mSvj/h0/L5QTy/8gAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_pre_huber,label='huber_pre')\n",
    "plt.plot(y_true,label='true')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "huber_EV = explained_variance_score(y_true, y_pre_huber)\n",
    "huber_MAE = mean_absolute_error(y_true, y_pre_huber)\n",
    "huber_MSE = mean_squared_error(y_true, y_pre_huber)\n",
    "huber_medAE = median_absolute_error(y_true, y_pre_huber)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "huber解释方差： 0.763647643192626\n",
      "huber平均绝对误差： 3.0590091454774604\n",
      "huber平均平方误差： 2.2956862269292095\n",
      "huber中位绝对误差： 18.494492080335544\n"
     ]
    }
   ],
   "source": [
    "print(\"huber解释方差：\", huber_EV)\n",
    "print(\"huber平均绝对误差：\", huber_MAE)\n",
    "print(\"huber平均平方误差：\", huber_medAE)\n",
    "print(\"huber中位绝对误差：\", huber_MSE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# -----------------------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.tree import DecisionTreeRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "decision = DecisionTreeRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DecisionTreeRegressor(criterion='mse', max_depth=None, max_features=None,\n",
       "           max_leaf_nodes=None, min_impurity_decrease=0.0,\n",
       "           min_impurity_split=None, min_samples_leaf=1,\n",
       "           min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
       "           presort=False, random_state=None, splitter='best')"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "decision.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pre_decision = decision.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x21760151ac8>"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_pre_decision,label='decision_pre')\n",
    "plt.plot(y_true,label='true')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "decision_EV = explained_variance_score(y_true, y_pre_decision)\n",
    "decision_MAE = mean_absolute_error(y_true, y_pre_decision)\n",
    "decision_MSE = mean_squared_error(y_true, y_pre_decision)\n",
    "decision_medAE = median_absolute_error(y_true, y_pre_decision)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "decison解释方差： 0.8707831357671765\n",
      "decison平均绝对误差差： 2.4196078431372556\n",
      "decison平均平方误差： 1.9000000000000021\n",
      "decison中位绝对误差： 9.807450980392158\n"
     ]
    }
   ],
   "source": [
    "print(\"decison解释方差：\", decision_EV)\n",
    "print(\"decison平均绝对误差差：\", decision_MAE)\n",
    "print(\"decison平均平方误差：\", decision_medAE)\n",
    "print(\"decison中位绝对误差：\", decision_MSE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# -----------------------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.svm import SVR"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "svr = SVR()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVR(C=1.0, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='auto',\n",
       "  kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "svr.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pre_svr = svr.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x217601b2dd8>"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_pre_svr,label='svr_pre')\n",
    "plt.plot(y_true,label='true')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "svr_EV = explained_variance_score(y_true, y_pre_svr)\n",
    "svr_MAE = mean_absolute_error(y_true, y_pre_svr)\n",
    "svr_MSE = mean_squared_error(y_true, y_pre_svr)\n",
    "svr_medAE = median_absolute_error(y_true, y_pre_svr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "svr解释方差： 0.04998748152991794\n",
      "svr平均绝对误差差： 6.523892883563182\n",
      "svr平均平方误差： 5.276791950787203\n",
      "svr中位绝对误差： 74.44368322028579\n"
     ]
    }
   ],
   "source": [
    "print(\"svr解释方差：\", svr_EV)\n",
    "print(\"svr平均绝对误差差：\", svr_MAE)\n",
    "print(\"svr平均平方误差：\", svr_medAE)\n",
    "print(\"svr中位绝对误差：\", svr_MSE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# -----------------------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neighbors import KNeighborsRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn = KNeighborsRegressor()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',\n",
       "          metric_params=None, n_jobs=1, n_neighbors=5, p=2,\n",
       "          weights='uniform')"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "knn.fit(X_train, y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pre_knn = knn.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2176021afd0>"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_pre_knn,label='knn_pre')\n",
    "plt.plot(y_true,label='true')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "knn_EV = explained_variance_score(y_true, y_pre_knn)\n",
    "knn_MAE = mean_absolute_error(y_true, y_pre_knn)\n",
    "knn_MSE = mean_squared_error(y_true, y_pre_knn)\n",
    "knn_medAE = median_absolute_error(y_true, y_pre_knn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "knn解释方差： 0.471795659702121\n",
      "knn平均绝对误差差： 4.540392156862745\n",
      "knn平均平方误差： 2.9800000000000004\n",
      "knn中位绝对误差： 40.059843137254894\n"
     ]
    }
   ],
   "source": [
    "print(\"knn解释方差：\", knn_EV)\n",
    "print(\"knn平均绝对误差差：\", knn_MAE)\n",
    "print(\"knn平均平方误差：\", knn_medAE)\n",
    "print(\"knn中位绝对误差：\", knn_MSE)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# -----------------------------------------------------------"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.neural_network import MLPRegressor\n",
    "from sklearn import preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "ss_x = preprocessing.StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_x_disorder = ss_x.fit_transform(X_train)\n",
    "test_x_disorder = ss_x.transform(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "ss_y = preprocessing.StandardScaler()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_y_disorder = ss_y.fit_transform(y_train.reshape(-1, 1))\n",
    "test_y_disorder = ss_y.transform(y_true.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "clf = MLPRegressor(solver = 'lbfgs', hidden_layer_sizes = (20, 20, 20), random_state = 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MLPRegressor(activation='relu', alpha=0.0001, batch_size='auto', beta_1=0.9,\n",
       "       beta_2=0.999, early_stopping=False, epsilon=1e-08,\n",
       "       hidden_layer_sizes=(20, 20, 20), learning_rate='constant',\n",
       "       learning_rate_init=0.001, max_iter=200, momentum=0.9,\n",
       "       nesterovs_momentum=True, power_t=0.5, random_state=1, shuffle=True,\n",
       "       solver='lbfgs', tol=0.0001, validation_fraction=0.1, verbose=False,\n",
       "       warm_start=False)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.fit(train_x_disorder, train_y_disorder.ravel())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pre_clf = clf.predict(x_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x21760c7c5c0>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(y_true, label = 'true')\n",
    "plt.plot(y_pre_clf, label = 'Netural Network pre')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Netural Network\n",
      "MSE均方误差： 2858.0777164887936\n",
      "MAE平均绝对误差： 45.74120332875365\n",
      "MedAE中位绝对误差： 49.24863919054539\n",
      "EV解释误差： -9.097631202444127\n"
     ]
    }
   ],
   "source": [
    "print(\"Netural Network\")\n",
    "print(\"MSE均方误差：\", mean_squared_error(y_true, y_pre_clf))\n",
    "print(\"MAE平均绝对误差：\", mean_absolute_error(y_true, y_pre_clf))\n",
    "print(\"MedAE中位绝对误差：\", median_absolute_error(y_true, y_pre_clf))\n",
    "print(\"EV解释误差：\", explained_variance_score(y_true, y_pre_clf))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
